45 research outputs found

    A Current Induced Transition in atomic-sized contacts of metallic Alloys

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    We have measured conductance histograms of atomic point contacts made from the noble-transition metal alloys CuNi, AgPd, and AuPt for a concentration ratio of 1:1. For all alloys these histograms at low bias voltage (below 300 mV) resemble those of the noble metals whereas at high bias (above 300 mV) they resemble those of the transition metals. We interpret this effect as a change in the composition of the point contact with bias voltage. We discuss possible explanations in terms of electromigration and differential diffusion induced by current heating.Comment: 5 pages, 6 figure

    Cohesive laws describing the interface behaviour of iron/precipitate interfaces under mixed loading conditions

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    The behaviour of 11 differently oriented iron-precipitate interfaces under mixed loading conditions is studied with molecular dynamics simulations. We find that the interface structure and the change in this structure play a key role in the response to the loading. The structure change is influenced by both the loading history and the loading direction. Depending on the interface and the loading direction, the presence of a dislocation at the interface may have an additional influence on the structure change. We update our previously derived cohesive laws for pure shear and pure tensile loading to take into account the influence of the other loading direction on the behaviour during mixed loading conditions. However, not for every interface a unique relation exists between the separations at the interface and the tractions. In those cases our cohesive laws give no exact prediction, but rather a range of possible values. The cohesive laws are intended to be used in numerical methods at the next larger length scale, such as discrete dislocation plasticity.Accepted Author Manuscript(OLD) MSE-

    Characterization of free volume in atomic models of metallic glasses

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    Freestyle data fitting and global temperatures

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    The method described here separates signal (trend) from noise in a set of measured bivariate data when there is no mathematical model for that signal. A computer program called spline2 implements the algorithm, which the authors apply to laboratory and realworld example problems.Materials Science and EngineeringMechanical, Maritime and Materials Engineerin
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